Data Scientist - Conversational AI and Agentic Workflows

Job Overview:

We are seeking an agile and skilled Data Scientist to join a high-velocity project team. The ideal candidate will help build advanced agentic workflows, utilizing LLMs as part of an innovative Retrieval-Augmented Generation (RAG) approach. This position offers the opportunity to work on groundbreaking technologies that enhance AI-driven solutions.

Key Responsibilities:

• Agentic Framework Development:
• Build and enhance an agentic framework that enables conversational AI to intelligently select and utilize tools and APIs through advanced reasoning.
• Information Retrieval Orchestration:
• Leverage orchestration frameworks such as Llama Index, LangChain, or similar to implement and manage Retrieval-Augmented Generation (RAG) techniques.
• Experimentation and Analysis:
• Conduct experiments to improve the agentic architecture and optimize RAG strategies.
• Analyze experimental results to enhance the accuracy, reliability, and performance of conversational AI models.

Technical Expertise:

• Programming Skills:
• Strong proficiency in Python.
• Experience with LLM Ops libraries such as LangChain, LlamaIndex, or similar tools is preferred. Alternatively, familiarity with machine learning libraries like Scikit-learn, Pandas, etc., is required.
• LLM and LLM Ops Knowledge:
• Strong understanding of Large Language Models and their applications, including experience with LLM operations, fine-tuning, and deployment.
• Tool Proficiency:
• Hands-on experience with tools like Llama Index and LangChain is preferred.
• Solid knowledge of Retrieval-Augmented Generation (RAG) techniques and their implementation.

Preferred Qualifications:

• Conversational AI Experience:
• Prior experience developing conversational AI applications or chatbots.
• Cloud Platform Expertise:
• Experience working with cloud platforms, preferably AWS. Familiarity with Azure or Google Cloud Platform (GCP) is a plus.

Desired Attributes:

• Agility and Quick Learning:
• Ability to quickly grasp and apply new technologies in a dynamic environment.
• Problem-Solving Skills:
• Strong analytical and reasoning skills for tackling complex technical challenges.
• Collaborative Mindset:
• Excellent communication skills and a team-oriented approach to drive collective success.